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International Conference on Computer Vision and Graphics

ICCVG 2016: Computer Vision and Graphics pp 86–94Cite as

Calibration of Structural Similarity Index Metric to Detect Artefacts in Game Engines

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9972))

Abstract

Previous studies reveal that Image Quality Metics (IQMs) can be efficiently used to automatically detect perceptual visibility of artefacts in the game engines. Very good matching was achieved for shadow acne, peter panning, and Z-fighting deteriorations, while IQM with the best detection rate proved to be the Structural Similarity Index Metric (SSIM). However, this metric generates noticeably worse results for the aliasing. Using SSIM, the artefacts are identified as differences in intensity, contrast, and structure between an image with deterioration and the corresponding reference. In this work we calibrate SSIM to improve matching for aliasing artefacts. We compare results generated by SSIM with the reference data created during subjective experiments in which people manually mark the visible local artefacts in the screenshots from game engines. In other words, we maximise convergence in the detection between the maps created by humans and computed by SSIM. The results of the cross-validation performed on a large collection of examples revealed that AUC (area under curve) in the receiver-operator analysis can be improved from 0.92 for default SSIM parameters to 0.97 for optimised parameters.

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Acknowledgement

The project was partially funded by the Polish National Science Centre (grant number DEC-2013/09/B/ST6/02270).

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Authors and Affiliations

  1. Faculty of Computer Science and Information Technology, West–Pomeranian University of Technology, Żołnierska Str. 49, 71–210, Szczecin, Poland

    Rafał Piórkowski & Radosław Mantiuk

Authors
  1. Rafał Piórkowski
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  2. Radosław Mantiuk
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Corresponding author

Correspondence to Radosław Mantiuk .

Editor information

Editors and Affiliations

  1. Faculty of Applied Informatics and Math, Warsaw University of Life Sciences , Warsaw, Poland

    Leszek J. Chmielewski

  2. Computer Sci and Software Engineering, University of Western Australia , Perth, Australia

    Amitava Datta

  3. Faculty of Applied Informatics and Math, Warsaw University of Life Sciences SGGW , Warsaw, Poland

    Ryszard Kozera

  4. Institute of Computer Science, Silesian University of Technology , Gliwice, Poland

    Konrad Wojciechowski

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Piórkowski, R., Mantiuk, R. (2016). Calibration of Structural Similarity Index Metric to Detect Artefacts in Game Engines. In: Chmielewski, L., Datta, A., Kozera, R., Wojciechowski, K. (eds) Computer Vision and Graphics. ICCVG 2016. Lecture Notes in Computer Science(), vol 9972. Springer, Cham. https://doi.org/10.1007/978-3-319-46418-3_8

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  • DOI: https://doi.org/10.1007/978-3-319-46418-3_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-46417-6

  • Online ISBN: 978-3-319-46418-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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